5 Things: Ethics, Morality and Truth

Posted: October 13, 2014 | Author: | Filed under: Education | Tags: , , , , , , , , , , , , | Leave a comment

Sometimes the only exposure my students will have to the study of ethics is (sorry, ethical philosophers) me and my “freeze-dried, snap-frozen, instant peas” version of the study of ethical issues. (In the land of the unethical, the mono-principled man is king?)

Tasty, tasty, frozen peas. Hey, is that Diogenes?

Tasty, tasty, frozen peas. Hey, is that Diogenes?

Here are a quick five things that loosely summarise my loose summaries.

  1. Ethics, Morals and Truth are Different Things. Morals are a person’s standards of belief concerning acceptable behaviour (we often throw around words like good and bad here). Ethics are the set of moral principles that guide a person’s behaviour or that of a group. Truth is the set of things that are real and factual, or those things that are accepted as true. Does that clear it up? Things that are true can be part of an unethical set of beliefs put together by immoral people. Immoral people can actually behave ethically consistently while still appear unethical and immoral from your group. Ethics often require you to start juggling things to work out a best or most consistent course of action, which is a luxury that we generally don’t have with the truth.
  2. Being Good is Not the Same Thing as Trying to Do the Right Thing. Trying to do the right thing is the field where your actions are guided by your ethical principles. Trying to be the best person you can be (Hello, Captain America) is virtue ethics. Both being good and doing the right thing can be guided by rules or by looking at outcomes but one is concerned who you are trying to be and the other is concerned with what you are trying to do. Yes, this means you can be a total ratbag as long as you behave the right way in the face of every ethical dilemma. (My apologies to any rats with bags.)
  3. You Can Follow Rules Or You Can Aim For The Best Outcome (Or Do Both, Actually). There are two basic breakdowns I’ve mentioned before: one follows rules and by doing that then the outcome doesn’t matter, the other tries to get the best outcome and this excuses any rules you break on the way to your good outcome. Or you can mix them together and hybridise it, even throwing in virtue ethics, which is what we tend to do because very few of us are moral philosophers and most of us are human beings. 🙂
  4. Consistency is Important. If you make decisions one way when it’s you and another way when it’s someone else then there’s a very good chance that you’re not applying a consistent ethical framework, you’re rationalising. (Often referred to as special pleading because you are special and different.) If you treat one group of people one way, and another completely differently, then I think you can guess that your ethics are too heavily biassed to actually be considered consistent – or all that ethical.
  5. Questioning Your Existing Frameworks Can Be Very Important. The chances that you managed to get everything right as you moved into adulthood is, really, surprisingly low, especially as most ethical and moral thinking is done in response to situations in your life. However, it’s important to think about how you can change your thinking in a way that forms a sound and consistent basis to build your ethical thinking upon. This can be very, very challenging, especially when the situation you’re involved in is particular painful or terrifying.

And that’s it. A rapid, shallow run through a deeply complex and rewarding area that everyone should delve into at some stage in their lives.

Tukhta: the tyranny of inflated performance figures.

Posted: October 13, 2014 | Author: | Filed under: Education | Tags: , , , , , , , , , , , , , , , , , , , , | 7 Comments

I’m sketching out a book on the early Soviet Union and artistic movements (don’t ask) so I’ve been rereading every Russian author I can get my hands on. I read a lot of these works when I was (probably too) young, starting from the very easy and shallow slopes of “Ivan Denisovich” and then plunging down into “Gulag Archipelago”. One of the things that comes out starkly from Solzhenitsyn’s account of the forced labour camps of “Gulag Archipelago” is the way that unrealistic expectations from an overbearing superior organisation can easily lead to an artificial conformity to productivity requirements, which leads to people cheating to achieve their overly ambitious quotas. In Solzhenitsyn’s words, the many thieves in the camp (he is less than complementary about non-political prisoners) coined the word tufta, which he rendered into better Russian as tukhta, the practice of making up your quotas through devious means and fabricating outputs. This could be as simple as writing down a figure that didn’t reflect your actual labour or picking up a pile of timber that had already been counted, moving it somewhere else, and counting it again.

The biggest problem with achieving a unreasonable goal, especially one which is defined by ideology rather than reality, is that it is easy for those who can to raise the expectation because, if you can achieve that goal, then no doubt you can achieve this one. This led to such excesses as the Stakhanovite movement, where patently impossible levels of human endeavour were achieved as evidence of commitment to Stalinist ideology and being a good member of the state. The darker side to all this, and this will be a word very familiar to those used to Soviet history, is that anyone who doesn’t attain such lofty goals or doesn’t sign up to be a noble Stakhanovite is labelled as a wrecker. Wreckers were a very common obstacle in the early development of the new Soviet state, pointing out things like “you can’t build that without concrete” or “water flows downhill”.  It should be noted that the original directives of the movement were quite noble, as represented in this extract from a conference in 1935:

The Stakhanovite movement means organizing labor in a new fashion, rationalizing technologic processes, correct division of labor, liberating qualified workers from secondary spadework, improving work place, providing rapid growth for labor productivity and securing significant increase of workers’ salaries.

Pretty good, right? Now consider that the namer of this movement was “Aleksei Stakhanov, who had mined 102 tons of coal in less than 6 hours (14 times his quota)”. This astounding feat of human endeavour was broken a year later, when Nikita Izotov mined 607 tons of coal in a single shift! It’s worth noting that fully-mechanised and highly industrialised contemporary Australian coal mines can produce round about 3,800 tonnes every 6 hours. What a paltry achievement when all you need is six Nikita Izotovs. So this seemingly well-focused initiative, structured as a benefit to state and worker, is disingenuous for the state and dangerous for the worker.

""Stakhanovite model soviet worker guarantees the continuing peace!"" You'll note the anti-intelligensia and racist targets of the worker - ideologically these were all wreckers.

“”Stakhanovite model soviet worker guarantees the continuing peace!””
You’ll note the anti-intelligensia and racist imagery on the poster as well – ideologically these were all wreckers.

Imagine that you are a worker trying to keep yourself and your family alive in the middle of famine after famine – of course you want to meet the requirements as well as you can, potentially even exceeding them so that you don’t get sent to a camp, locked up, or demoted and diminished in your role. While some people might be practising tukhta out of laziness, you are practising it because it is the way that things are. You need to nod in agreement with ridiculous requirements and then write up your results in a way that exceeds them, if you want to survive. Your reward? Even more ridiculous requirements, not determined in capacity and available inputs but in required output. Tukhta is your curse and your only means of survival. Unsurprisingly, the Stakhanovite movement was denounced as part of Stalinism later on in the emerging and mutating Soviet Union.

Now imagine that you are a student. You have been given a pile of reading to do, a large collection of assignments across a variety of subjects that are not really linked to each other, and you are told that you need to do all of this to succeed. Are you going to deeply apply yourself to everything, to form your own conceptual framework and illuminate it through careful study? Well, perhaps you would, except that you have quotas to achieve and deadlines to meet and, around you, other students are doing better, pressing further and are being actively rewarded and encouraged for it. Will you be at least tempted to move things around to achieve your quota? Will you prioritise some labour over another, which could be more useful in the long-term? Will you hide your questions in the hope of being able to be seen to not be a bad student?

Now imagine that you are a young academic, perhaps one with a young family, and you are going to enter the job market. You know that your publications, research funding and overall contributions will be compared to other stand-outs in the field, to overall averages and to defined requirements for the institution. Will you sit and mull contemplatively over an important point of science or will you crank out yet another journal at a prestigious, but not overly useful, target venue, working into the night and across the weekend? Will you look at the exalted “Research Stars” who have very high publication and citation rates and who attract salary loadings up to a level that could pay for 2-3 times the number of positions they hold? Will you be compared to these people and found wanting? Will you write papers with anyone prestigious? Will you do what you need to do to move from promising to reliable to a leader in the field regardless of whether it’s actually something you should be doing? (Do you secretly wonder whether you can even get there from where you started and lie awake at night thinking about it?)

Measurements that pit us against almost impossible standards and stars so high that we probably cannot reach them grind down the souls of the majority of the population and lead them into the dark pathways of tukhta. It is easy to say “Don’t cheat” or “Don’t work all weekend” when you are on top of the pile. As the workers in the Gulag and many Soviet Citizens found out, doing that just lets the people setting the quotas to keep setting them as they wish, with no concern for the people who are grist to the mill.

Tukhta should not be part of an educational system and we should be very wary of the creeping mensuration of the academy. You don’t have to look far to see highly celebrated academics and researchers who were detected in their cheating and were punished hard. Yet a part of me knows that the averages are set as much by the tukhtaviks that we have not yet detected and, given how comparative was have made our systems, that is monstrously unfair.

Assessing how well someone is performing needs to move beyond systems that are so pitifully easy to game and so terribly awful to their victims when they are so gamed.

The Fragile Student Relationship (working from #Unstuck #by Julie Felner @felner)

Posted: September 18, 2014 | Author: | Filed under: Education, Opinion | Tags: , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

I was referred some time ago to a great site called “Unstuck”, which has some accompanying iPad software, that helps you to think about how to move past those stuck moments in your life and career to get things going. They recently posted an interesting item on “How to work like a human” and I thought that a lot of what they talked about had direct relevance to how we treat students and how we work with them to achieve things. The article is by Julie Felner and I strongly suggest that you read it, but here are my thoughts on her headings, as they apply to education and students.

Ultimately, if we all work together like human beings, we’re going to get on better than if we treat our students as answer machines and they treat us as certification machines. Here’s what optimising for one thing, mechanistically, can get you:

This robot is the business at climbing hills. Dancing like a fool, not so much. It's not human.

This robot is the business at climbing hills. Dancing like a fool, not so much. It’s not human.

But if we’re going to be human, we need to be connected. Here are some signs that you’re not really connected to your students.

  1. Anything that’s not work you treat with a one word response. A student comes to see you and you don’t have time to talk about anything but assignment X or project Y. I realise time is scarce but, if we’re trying to build people, we have to talk to people, like people.
  2. You’re impatient when they take time to learn or adjust. Oh yeah, we’ve all done this. How can they not pick it up immediately? What’s wrong with them? Don’t they know I’m busy?
  3. Sleep and food are for the weak – and don’t get sick. There are no human-centred reasons for not getting something done. I’m scheduling all of these activities back-to-back for two months. If you want it, you’ll work for it.
  4. We never ask how the students are doing. By which I mean, asking genuinely and eking out a genuine response, if some prodding is required. Not intrusively but out of genuine interest. How are they doing with this course?
  5. We shut them down. Here’s the criticism. No, I don’t care about the response. No, that’s it. We’re done. End of discussion. There are times when we do have to drawn an end to a discussion but there’s a big difference between closing off something that’s going nowhere and delivering everything as if no discussion is possible.

Here is my take on Julie’s suggestions for how we can be more human at work, which works for the Higher Ed community just as well.

  1. Treat every relationship as one that matters. The squeaky wheels and the high achievers get a lot of our time but all of our students are actually entitled to have the same level of relationship with us. Is it easy to get that balance? No. Is it a worthwhile goal? Yes.
  2. Generously and regularly express your gratitude. When students do something well, we should let them know- as soon as possible. I regularly thank my students for good attendance, handing things in on time, making good contributions and doing the prep work. Yes, they should be doing it but let’s not get into how many things that should be done aren’t done. I believe in this strongly and it’s one of the easiest things to start doing straight away.
  3. Don’t be too rigid about your interactions. We all have time issues but maybe you can see students and talk to them when you pass them in the corridor, if both of you have time. If someone’s been trying to see you, can you grab them from a work area or make a few minutes before or after a lecture? Can you talk with them over lunch if you’re both really pressed for time? It’s one thing to have consulting hours but it’s another to make yourself totally unavailable outside of that time. When students are seeking help, it’s when they need help the most. Always convenient? No. Always impossible to manage? No. Probably useful? Yes.
  4. Don’t pretend to be perfect. Firstly, students generally know when you’re lying to them and especially when you’re fudging your answers. Don’t know the answer? Let them know, look it up and respond when you do. Don’t know much about the course itself? Well, finding out before you start teaching is a really good idea because otherwise you’re going to be saying “I don’t know a lot” and there’s a big, big gap between showing your humanity and obviously not caring about your teaching. Fix problems when they arise and don’t try to make it appear that it wasn’t a problem. Be as honest as you can about that in your particular circumstances (some teaching environments have more disciplinary implications than others and I do get that).
  5. Make fewer assumptions about your students and ask more questions. The demographics of our student body have shifted. More of my students are in part-time or full-time work. More are older. More are married. Not all of them have gone through a particular elective path. Not every previous course contains the same materials it did 10 years ago. Every time a colleague starts a sentence with “I would have thought” or “Surely”, they are (almost always) projecting their assumptions on to the student body, rather than asking “Have you”, “Did you” or “Do you know”?

Julie made the final point that sometimes we can’t get things done to the deadline. In her words:

You sometimes have to sacrifice a deadline in order to preserve something far more important — a relationship, a person’s well-being, the quality of the work

I completely agree because deadlines are a tool but, particularly in academia, the deadline is actually rarely as important as people. If our goal is to provide a good learning environment, working our students to zombie status because “that’s what happened to us” is bordering on a cycle of abuse, rather than a commitment to quality of education.

We all want to be human with our students because that’s how we’re most likely to get them to engage with us as a human too! I liked this article and I hope you enjoyed my take on it. Thank you, Julie Felner!

Knowing the Tricks Helps You To Deal With Assumptions

Posted: September 10, 2014 | Author: | Filed under: Education | Tags: , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

I teach a variety of courses, including one called Puzzle-Based Learning, where we try to teach think and problem-solving techniques through the use of simple puzzles that don’t depend on too much external information. These domain-free problems have most of the characteristics of more complicated problems but you don’t have to be an expert in the specific area of knowledge to attempt them. The other thing that we’ve noticed over time is that a good puzzle is fun to solve, fun to teach and gets passed on to other people – a form of infectious knowledge.

Some of the most challenging areas to try and teach into are those that deal with probability and statistics, as I’ve touched on before in this post. As always, when an area is harder to understand, it actually requires us to teach better but I do draw the line at trying to coerce students into believing me through the power of my mind alone. But there are some very handy ways to show students that their assumptions about the nature of probability (and randomness) so that they are receptive to the idea that their models could need improvement (allowing us to work in that uncertainty) and can also start to understand probability correctly.

We are ferociously good pattern matchers and this means that we have some quite interesting biases in the way that we think about the world, especially when we try to think about random numbers, or random selections of things.

So, please humour me for a moment. I have flipped a coin five times and recorded the outcome here. But I have also made up three other sequences. Look at the four sequences for a moment and pick which one is most likely to be the one I generated at random – don’t think too much, use your gut:

  1. Tails Tails Tails Heads Tails
  2. Tails Heads Tails Heads Heads
  3. Heads Heads Tails Heads Tails
  4. Heads Heads Heads Heads Heads

Have you done it?

I’m just going to put a bit more working in here to make sure that you’ve written down your number…

I’ve run this with students and I’ve asked them to produce a sequence by flipping coins then produce a false sequence by making subtle changes to the generated one (turns heads into tails but change a couple along the way). They then write the two together on a board and people have to vote on which one is which. As it turns out, the chances of someone picking the right sequence is about 50/50, but I engineered that by starting from a generated sequence.

This is a fascinating article that looks at the overall behaviour of people. If you ask people to write down a five coin sequence that is random, 78% of them will start with heads. So, chances are, you’ve picked 3 or 4 as you’re starting sequence. When it comes to random sequences, most of us equate random with well-shuffled, and, on the large scale, 30 times as many people would prefer option 3 to option 4. (This is where someone leaps into the comments to say “A-ha” but, it’s ok, we’re talking about overall behavioural trends. Your individual experience and approach may not be the dominant behaviour.)

From a teaching point of view, this is a great way to break up the concepts of random sequences and some inherent notion that such sequences must be disordered. There are 32 different ways of flipping 5 coins in a strict sequence like this and all of them are equally likely. It’s only when we start talking about the likelihood of getting all heads versus not getting all heads that the aggregated event of “at least one head” starts to be more likely.

How can we use this? One way is getting students to write down their sequences and then asking them to stand up, then sit down when your ‘call’ (from a script) goes the other way. If almost everyone is still standing at heads then you’ve illustrated that you know something about how their “randomisers” work. A lot of people (if your class is big enough) should still be standing when the final coin is revealed and this we can address. Why do so many people think about it this way? Are we confusing random with chaotic?

The Law of Small Numbers (Tversky and Kahneman), also mentioned in the post, which is basically that people generalise too much from small samples and they expect small samples to act like big ones. In your head, if the grand pattern over time could be resorted into “heads, tails, heads, tails,…” then small sequences must match that or they just don’t look right. This is an example of the logical fallacy called a “hasty generalisation” but with a mathematical flavour. We are strongly biassed towards the the validity of our experiences, so when we generate a random sequence (or pick a lucky door or win the first time at poker machines) then we generalise from this small sample and can become quite resistant to other discussions of possible outcomes.

If you have really big classes (367 or more) then you can start a discussion on random numbers by asking people what the chances are that any two people in the room share a birthday. Given that there are only 366 possible birthdays, the Pigeonhole principle states that two people must share a birthday as, in a class of 367, there are only 366 birthdays to go around so one must be repeated! (Note for future readers: don’t try this in a class of clones.) There are lots of other, interesting thinking examples in the link to Wikipedia that helps you to frame randomness in a way that your students might be able to understand it better.

10 pigeons into 9 boxes? Someone has a roommate.

10 pigeons into 9 boxes? Someone has a roommate.

I’ve used a lot of techniques before, including the infamous card shouting, but the new approach from the podcast is a nice and novel angle to add some interest to a class where randomness can show up.

Funding Education: Trust me, you want to. #stem #education #csed

Posted: September 8, 2014 | Author: | Filed under: Education, Opinion | Tags: , , , , , , , , , , , , , , , , , | Leave a comment

Some very serious changes to the Higher Education system of Australia are going to be discussed starting from October 28th – deregulating the University fee structure, which will most likely lead to increasing fees and interest rates, leading to much greater student debt. (Yes, there are some positives in there but it’s hard to get away from massive increase of student debt.) While some university representative organisations are in favour of this, with amendments and protections for some students, I am yet to be convinced that deregulating the Universities is going to do much while we labour under the idea that students will move around based on selected specialisations,  the amount of “life lessons” they will accumulate or their perception of value for money. We have no idea what price sensitivity is going to do to the Australian market. We do know what happened in the UK when they deregulated fees:

‘Professor Byrne agreed, but said fee deregulation would have to be “carefully thought through so as to avoid what happened in the UK when they did it there – initially, when the fees were uncapped, all the universities just charged the maximum amount. It’s been corrected now, but that was a complete waste of time because all it did was transfer university costing from the public to the private sphere.”’

But, don’t worry, Professor Byrne doesn’t think this will lead to a two-tier system, split between wealthy universities and less-well-off regionals:

“I’d call it an appropriately differentiated system, with any number of levels within it.”

We have four classes! That must be better than have/have not. That’s… wait…

The core of this argument is that, somehow, it is not the role of Universities to provide the same thing as every other university, which is a slashing of services more usually (coyly) referred to as “playing to your strengths”. What this really is, however, is geographical and social entrapment. You weren’t born in a city, you don’t want to be saddled with huge debt or your school wasn’t great so you didn’t get the marks to go to a “full” University? Well, you can go to a regional University, which is playing to its strengths, to offer you a range of courses that have been market-determined to be suitable.  But it will be price competitive! This is great, because after 2-3 generations of this, the people near the regional University will not have the degree access to make the money to work anywhere other than their region or to go to a different University. And, of course, we have never seen a monopolised, deregulated market charging excessive fees when their consumer suffers from a lack of mobility…

There are some quite valid questions as to why we need to duplicate teaching capabilities in the same state, until we look at the Australian student, who tends to go to University near where they live, rather than moving into residential accommodation on campus, and, when you live in a city that spans 70km from North to South as Adelaide does, it suddenly becomes more evident why there might be repeated schools in the Universities that span this geographical divide. When you live in Sydney, where the commute can be diabolical and the city is highly divided by socioeconomic grouping, it becomes even more important. Duplication in Australian Universities is not redundancy, it’s equality.

The other minor thing to remember is that the word University comes from the Latin word for whole. The entire thing about a University is that it is most definitely not a vocational training college, focussed on one or two things. It is defined by, and gains strength from, its diversity and the nature of study and research that comes together in a place that isn’t quite like any other. We are at a point in history when the world is changing so quickly that predicting the jobs of the next 20 years is much harder, especially if we solve some key problems in robotics. Entire jobs, and types of job, will disappear almost overnight – if we have optimised our Universities to play to their strengths rather than keeping their ability to be agile and forward-looking, we will pay for it tomorrow. And we will pay dearly for it.

Education can be a challenging thing for some people to justify funding because you measure the money going in and you can’t easily measure the money that comes back to you. But we get so much back from an educated populace. Safety on the road: education. Safety in the skies: education. Art, literature, music, film: a lot of education. The Internet, your phone, your computer: education, Universities, progressive research funding and CSIRO.

Did you like a book recently? That was edited by someone who most likely had a degree that many wouldn’t consider worth funding. Just because it’s not obvious what people do with their degrees, and just because some jobs demand degrees when they don’t need them, it doesn’t mean that we need to cut down on the number of degrees or treat people who do degrees with a less directly vocational pathway as if they are parasites (bad) or mad (worse). Do we need to change some things about our society in terms of perceptions of worth and value? Yes – absolutely, yes. But let’s not blame education for how it gets mutated and used. And, please, just because we don’t understand someone’s job, let us never fall into the trap of thinking it’s easy or trivial.

The people who developed the first plane had never flown. The people who developed WiFi had never used a laptop. The people who developed the iPhone had never used one before. But they were educated and able to solve challenges using a combination of technical and non-technical knowledge. Steve Jobs may never have finished college (although he attributed the Mac’s type handling to time he spent in courses there) but he employed thousands of people who did – as did Bill Gates. As do all of the mining companies if they actually want to find ore bodies and attack them properly.

Education will define what Australia is for the rest of this century and for every century afterwards. To argue that we have to cut funding and force more debt on to students is to deny education to more Australians and, ultimately, to very much head towards a permanently divided Australia.

You might think, well, I’m ok, why should I worry? Ignoring any altruistic issues, what do you think an undereducated, effectively underclass, labour force is going to do when all of their jobs disappear? If there are still any History departments left, then you might want to look into the Luddites and the French Revolution. You can choose to do this for higher purposes, or you can do it for yourself, because education will help us all to adjust to an uncertain future and, whether you think so or not, we probably need the Universities running at full speed as cradles of research and ideas, working with industry to be as creative as possible to solve the problems that you will only read about in tomorrow’s paper.

Funding Education: Trust me, you want to.

Rage Against the Machine

Rage Against the Machine

I have a new book out: A Guide to Teaching Puzzle-based learning. #puzzlebasedlearning #education

Posted: September 5, 2014 | Author: | Filed under: Education, Opinion | Tags: , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

Time for some pretty shameless self-promotion. Feel free to stop reading if that will bother you.

My colleagues, Ed Meyer from BWU, Raja Sooriamurthi from CMU and Zbyszek Michalewicz (emeritus from my own institution) and I have just released a new book, called “A Guide to Teaching Puzzle-based learning.” What a labour of love this has been and, better yet, we are still still talking to each other. In fact, we’re planning some follow-up events next year to do some workshops around the book so it’ll be nice to work with the team again.

(How to get it? This is the link to Springer, paperback and e-Book. This is the link to Amazon, paperback only I believe.)

Here’s a slightly sleep-deprived and jet-lagged picture of me holding the book as part of my “wow, it got published” euphoria!

See how happy I am?

See how happy I am? And also so out of it.

The book is a resource for the teacher, although it’s written for teachers from primary to tertiary and it should be quite approachable for the home school environment as well. We spent a lot of time making it approachable, sharing tips for students and teachers alike, and trying to get all of our knowledge about how to teach well with puzzles down into the one volume. I think we pretty much succeeded. I’ve field-tested the material here at Universities, schools and businesses, with very good results across the board. We build on a good basis and we love sound practical advice. This is, very much, a book for the teaching coalface.

It’s great to finally have it all done and printed. The Springer team were really helpful and we’ve had a lot of patience from our commissioning editors as we discussed, argued and discussed again some of the best ways to put things into the written form. I can’t quite believe that we managed to get 350 pages down and done, even with all of the time that we had.

If you or your institution has a connection to SpringerLink then you can read it online as part of your subscription. Otherwise, if you’re keen, feel free to check out the preview on the home page and then you may find that there are a variety of prices available on the Web. I know how tight budgets are at the moment so, if you do feel like buying, please buy it at the best price for you. I’ve already had friends and colleagues ask what benefits me the most and the simple answer is “if people read it and find it useful”.

To end this disgraceful sales pitch, we’re actually quite happy to run workshops and the like, although we are currently split over two countries (sometimes three or even four), so some notice is always welcome.

That’s it, no more self-promotion to this extent until the next book!

 

Talking Ethics with the Terminator: Using Existing Student Experience to Drive Discussion

Posted: September 5, 2014 | Author: | Filed under: Education | Tags: , , , , , , , , , , , , , , , , , , , | Leave a comment

One of the big focuses at our University is the Small-Group Discovery Experience, an initiative from our overall strategy document, the Beacon of Enlightenment. You can read all of the details here, but the essence is that a small group of students and an experienced research academic meet regularly to start the students down the path of research, picking up skills in an active learning environment. In our school, I’ve run it twice as part of the professional ethics program. This second time around, I think it’s worth sharing what we did, as it seems to be working well.

Why ethics? Well, this is first year and it’s not all that easy to do research into Computing if you don’t have much foundation, but professional skills are part of our degree program so we looked at an exploration of ethics to build a foundation. We cover ethics in more detail in second and third year but it’s basically a quick “and this is ethics” lecture in first year that doesn’t give our students much room to explore the detail and, like many of the more intellectual topics we deal with, ethical understanding comes from contemplation and discussion – unless we just want to try to jam a badly fitting moral compass on to everyone and be done.

Ethical issues present the best way to talk about the area as an introduction as much of the formal terminology can be quite intimidating for students who regard themselves as CS majors or Engineers first, and may not even contemplate their role as moral philosophers. But real-world situations where ethical practice is more illuminating are often quite depressing and, from experience, sessions in medical ethics, and similar, rapidly close down discussion because it can be very upsetting. We took a different approach.

The essence of any good narrative is the tension that is generated from the conflict it contains and, in stories that revolve around artificial intelligence, robots and computers, this tension often comes from what are fundamentally ethical issues: the machine kills, the computer goes mad, the AI takes over the world. We decided to ask the students to find two works of fiction, from movies, TV shows, books and games, to look into the ethical situations contained in anything involving computers, AI and robots. Then we provided them with a short suggested list of 20 books and 20 movies to start from and let them go. Further guidance asked them to look into the active ethical agents in the story – who was doing what and what were the ethical issues?

I saw the students after they had submitted their two short paragraphs on this and I was absolutely blown out of the water by their informed, passionate and, above all, thoughtful answers to the questions. Debate kept breaking out on subtle points. The potted summary of ethics that I had given them (follow the rules, aim for good outcomes or be a good person – sorry, ethicists) provided enough detail for the students to identify issues in rule-based approaches, utilitarianism and virtue ethics, but I could then introduce terms to label what they had already done, as they were thinking about them.

I had 13 sessions with a total of 250 students and it was the most enjoyable teaching experience I’ve had all year. As follow-up, I asked the students to enter all of their thoughts on their entities of choice by rating their autonomy (freedom to act), responsibility (how much we could hold them to account) and perceived humanity, using a couple of examples to motivate a ranking system of 0-5. A toddler is completely free to act (5) and completely human (5) but can’t really be held responsible for much (0-1 depending on the toddler). An aircraft autopilot has no humanity or responsibility but it is completely autonomous when actually flying the plane – although it will disengage when things get too hard. A soldier obeying orders has an autonomy around 5. Keanu Reeves in the Matrix has a humanity of 4. At best.

They’ve now filled the database up with their thoughts and next week we’re going to discuss all of their 0-5 ratings as small groups, then place them on a giant timeline of achievements in literature, technology, AI and also listing major events such as wars, to see if we can explain why authors presented the work that they did. When did we start to regard machines as potentially human and what did the world seem like them to people who were there?

This was a lot of fun and, while it’s taken a little bit of setting up, this framework works well because students have seen quite a lot, the trick is just getting to think about with our ethical lens. Highly recommended.

What do you think, Arnold? (Image from moviequotes.me)

What do you think, Arnold? (Image from moviequotes.me)

Being Honest About Stress, Challenge and Humanity: R U OK? Day #ruok

Posted: August 26, 2014 | Author: | Filed under: Education, Opinion | Tags: , , , , , , , , , , , , , , , | Leave a comment

 

The RUOK™ logo from https://www.ruok.org.au

The RUOK™ logo from https://www.ruok.org.au

R U Ok? Day (September the 11th) is coming up soon, with its focus on reaching out and starting conversations with people that you think might not be ok, or might benefit from a friendly conversation. It’s a great initiative and, as someone who has struggled with mental illness, I’m so happy to see us talking openly about this. For me to out myself as having suffered with depression is no big thing, as I discuss it in other parts of the ‘net, but I realise that some of you might now look at what I do and what I say in a different light.

And, if you do, I have to tell you that you need to change the way that you think about these things. A very large number of humans will go through some form of mental issue in their lives, unsurprisingly given the levels of stress that we put ourselves under, the struggle some people have just to survive and the challenges that lie ahead of us as a rather greedy species on a finite globe. So, yes, I’ve suffered from depression but it is an illness. It is treatable and, when it is treated and managed, then you can’t tell that I have problems. In fact, like many people with the problem, even when I’m suffering, you wouldn’t really know. Nobody asks to get mentally ill so stigmatising, isolating and discriminating against people with a treatable mental condition is not just wrong, it’s pretty stupid. So let’s get beyond this and start talking, openly.

That’s where RUOK? is great because it gives you a day and some agency to reach out to someone who seems a little … off and ask them if they’re ok. Trust me when I say that 99% of them will appreciate it. Yes, 1% might give you some grief but if I knew a bet would pay off 99% of the time, I’d take it. The web site has some great tips for starting conversations so please read them if you’re thinking about doing this. (Pro tip: starting a conversation with “You should just cheer up” is not a great way to start. Or finish. In fact, just scratch that and try again.)

I am very open with my students, which I know some people think is potentially unprofessional, and I am a strong believer in cognitive apprenticeship. We are, pretty much, all the same in many respects and me pretending that everything I do comes fully formed and perfect from my amazing brain is a lie. My wisdom, such as it is, is the accumulated memory of the mistakes I’ve made that haven’t killed me yet. My students need to know that the people around them struggle, wonder, stress out and, quite frequently, rise above it all to keep on doing wonderful and beautiful things. I am still professional but I am honest and I am human.

I want to share with all of you something that I wrote on the death of Robin Williams, which I’ve edited slightly for language, but it’s been shared a lot over my other social feeds so it obviously resonates with people. However, many of my students won’t have seen it because I keep my private social life and ‘work’ social media separated. So here it is. I hope that you find it useful and, if you need help, maybe nudges you to help, and if you know someone you’re worried about, it inspires you to ask them “R U OK?”

Mental illness is a poisonous and weird thing. If your eyes changed function, you’d see things differently. When your brain changes function, everything gets weird – and the only impression you have of the perceptual world is suddenly flawed and untrustworthy. But it’s a biochemical issue like diabetes – regulatory systems that aren’t working properly and cannot just be “got over” by thinking happily. Ask a diabetic whether they’ve “really tried” to handle their sugar and see how far that gets you. 🙂

I wrote something, years ago, that I’ve never posted, to try and explain why some people just can’t stay. The nastiest thing about mental illness is that it can show you a world and a way of thinking that makes suicide apparently logical and, even more sadly, necessary. If you saw that world, then maybe you wouldn’t stay either. This doesn’t make it easier on the survivors but it’s important to recognise the role that an actual illness plays here. That f***ing ba***rd, cancer, takes people from us all the time but it at least has the decency to wield the knife itself. Depression puts the knife in the hands of its victim and makes it look like calculated agency, which hurts the people left behind even more.

There is no magic bullet for helping people with mental illness. Some need visible support. Some need solitude. Some need to work. Some drown in it. That’s because mental illness affects people, in all of their variety and their glorious irrationality, and I am no more a poster child for depression than anyone else. I can’t even tell you how to help me and, given how much I communicate, that’s the most irritating thing of all. But I do know that the ongoing support of caring people who are watching and listening makes a big difference and those of you who are aware and supporting, you keep up that good work! (And thank you, on behalf of the people who are still here because other people helped.)

It’s a sad day with Robin WIlliams passing but this is only a part of him. It’s a sad and mad part of him and I wish it hadn’t happened but I won’t let it define him, because his struggles were a part of him and his contribution to laughter and joy were so much greater. The least I can do is to see past his ‘mental diabetes’ to celebrate his actual talent and contribution. And offer my deepest sympathies and condolences to his family and friends.

Rest well, Robin.

 

ITiCSE 2014, Day 3, Final Session, “CS Ed Research”, #ITiCSE2014 #ITiCSE

Posted: June 26, 2014 | Author: | Filed under: Education | Tags: , , , , , , , , , , , , , , , , , | Leave a comment

The first paper, in the final session, was the “Effect of a 2-week Scratch Intervention in CS1 on Learners with Varying Prior Knowledge”, presented by Shitanshu Mirha, from IIT Bombay. The CS1 course context is a single programming course for all freshmen engineer students, thus it has to work for novice and advanced learners. It’s the usual problem: novices get daunted and advanced learners get bored. (We had this problem in the past.) The proposed solution is to use Scratch, because it’s low-floor (easy to get started), high-ceiling (can build complex projects) and wide-walls (applies to a wide variety of topics and themes). Thus it should work for both novice and advanced learners.

The theoretical underpinning is that novice learners reach cognitive overload while trying to learn techniques for programming and a language at the same time. One way to reduce cognitive load is to use visual programming environments such as Scratch. For advanced learners, Scratch can provide a sufficiently challenging set of learning material. From the perspective of Flow theory, students need to reach equilibrium between challenge level and perceived skill.

The research goal was to investigate the impact of a two-week intervention in a college course that will transition to C++. What would novices learn in terms of concepts and C++ transition? What would advanced students learn? What was the overall impact on students?

The cohort was 450 students, no CS majors, with a variety of advanced and novice learners, with a course objective of teaching programming in C++ across 14 weeks. The Scratch intervention took place over the first four weeks in terms of teaching and assessment. Novice scaffolding was achieved by ramping up over the teaching time. Engagement for advanced learners was achieved by starting the project early (second week). Students were assessed by quizzes, midterms and project production, with very high quality projects being demonstrated as Hall of Fame projects.

Students were also asked to generate questions on what they learned and these could be used for other students to practice with. A survey was given to determine student perception of usefulness of the Scratch approach.

The results for Novices were presented. While the Novices were able to catch up in basic Scratch comprehension (predict output and debug code), this didn’t translate into writing code in Scratch or debugging programs in C++. For question generation, Novices were comparable to advanced learners in terms of number of questions generated on sequences, conditionals and data. For threads, events and operators, Novices generated more questions – although I’m not sure I see the link that demonstrates that they definitely understood the material. Unsurprisingly, given the writing code results, Novices were weaker in loops and similar programming constructs. More than 53% of Novices though the Scratch framing was useful.

In terms of Advanced learner engagement, there were more Advanced projects generated. Unsurprisingly, Advanced projects were far more complicated. (I missed something about Most-Loved projects here. Clarification in the comments please!) I don’t really see how this measures engagement – it may just be measuring the greater experience.

Summarising, Scratch seemed to help Novices but not with actual coding or working with C++, but it was useful for basic concepts. The author claims that the larger complexity of Advanced user projects shows increased engagement but I don’t believe that they’ve presented enough here to show that. The sting in the tail is that the Scratch intervention did not help the Novices catch up to the Advanced users for the type of programming questions that they would see in the exam – hence, you really have to question its utility.

The next paper is “Enhancing Syntax Error Messages Appears Ineffectual” presented by Paul Denny, from The University of Auckland. Apparently we could only have one of Paul or Andrew Luxton-Reilly, so it would be churlish to say anything other than hooray for Paul! (Those in the room will understand this. Sorry we missed you, Andrew! Catch up soon.) Paul described this as the least impressive title in the conference but that’s just what science is sometimes.

Java is the teaching language at Auckland, about to switch to Python, which means no fancy IDEs like Scratch or Greenfoot. Paul started by discussing a Java statement with a syntax error in it, which gave two different (but equally unhelpful) error messages for the same error.

if (a < 0) || (a > 100)
  error=true;

// The error is in the top line because there should be surrounding parentheses around conditions
// One compiler will report that a ';' is required at the ||, which doesn't solve the right problem.
// The other compiler says that another if statement is required at the ||
// Both of these are unhelpful - as well as being wrong. It wasn't what we intended.

The conclusion (given early) is simple: enhancing the error messages with a controlled empirical study found no significant effect. This work came from thinking about an early programming exercise that was quite straightforward but seemed to came students a lot of grief. For those who don’t know, programs won’t run until we fix the structural problems in how we put the program elements together: syntax errors have to be fixed before the program will run. Until the program runs, we get no useful feedback, just (often cryptic) error messages from the compiler. Students will give up if they don’t make progress in a reasonable interval and a lack of feedback is very disheartening.

The hypothesis was that providing more useful error messages for syntax errors would “help” users, help being hard to quantify. These messages should be:

  • useful: simple language, informal language and targeting errors that are common in practice. Also providing example code to guide students.
  • helpful: reduce the number of non-compiling submissions in total, reduce number of consecutive non-compiling submissions AND reduce the number of attempts to resolve a specific error.

In related work, Kummerfeld and Kay (ACE 2003), “The neglected battle fields of Syntax Errors”, provided a web-based reference guide to search for the error text and then get some examples. (These days, we’d probably call this Stack Overflow. 🙂 ) Flowers, Carver and Jackson, 2004, developed Gauntlet to provide more informal error messages with user-friendly feedback and humour. The paper was published in Frontiers in Education, 2004, “Empowering Students and Building Confidence in Novice Programmers Through Gauntlet.” The next aspect of related work was from Tom Schorsch, SIGCSE 1995, with CAP, making specific corrections in an environment. Warren Toomey modified BlueJ to change the error subsystem but there’s no apparent published work on this. The final two were Dy and Rodrigo, Koli Calling 2010, with a detector for non-literal Java errors and Debugging Tutor: Preliminary evaluation, by Carter and Blank, KCSC, January 2014.

The work done by the authors was in CodeWrite (written up in SIGCSE 2011 and ITiCSE 2011, both under Denny et al). All students submit non-compiling code frequently. Maybe better feedback will help and influence existing systems such as Nifty reflections (cloud bat) and CloudCoder. In the study, student had 10 problems they could choose from, with a method, description and return result. The students were split in an A/B test, where half saw raw feedback and half saw the enhanced message. The team built an error recogniser that analysed over 12,000 submissions with syntax errors from a 2012 course and the raw compiler message identified errors 78% of the time. (“All Syntax Errors are Not Equal”, ITiCSE 2012). In other cases, static analysis was used to work out what the error was. Eventually, 92% of the errors were classifiable from the 2012 dataset. Anything not in that group was shown as raw error message to the student.

In the randomised controlled experiment, 83 students had to complete the 10 exercises (worth 1% each), using the measures of:

  • number of consecutive non-compiing submissions for each exercise
  • Total number of non-compiling submissions
  • … and others.

Do students even read the error messages? This would explain the lack of impact. However, examining student code change there appears to be a response to the error messages received, although this can be a slow and piecemeal approach. There was a difference between the groups, but it wasn’t significant, because there was a 17% reduction in non-compiling submissions.

I find this very interesting because the lack of significance is slightly unexpected, given that increased expressiveness and ease of reading should make it easier for people to find errors, especially with the provision of examples. I’m not sure that this is the last word on this (and I’m certainly not saying the authors are wrong because this work is very rigorous) but I wonder what we could be measuring to nail this one down into the coffin.

The final talk was “A Qualitative Think-Aloud Study of Novice Programmers’ Code Writing Strategies”, which was presented by Tony Clear, on behalf of the authors. The aim of the work was to move beyond the notion of levels of development and attempt to explore the process of learning, building on the notion of schemas and plans. Assimilation (using existing schemas to understand new information) and accommodation  (new information won’t fit so we change our schema) are common themes in psychology of learning.

We’re really not sure how novice programmers construct new knowledge and we don’t fully understand the cognitive process. We do know that learning to program is often perceived as hard. (Shh, don’t tell anyone.) At early stages, movie programmers have very few schemas to draw on, their knowledge is fragile and the cognitive load is very high.

Woohoo, Vygotsky reference to the Zone of Proximal Development – there are things students know, things that can learn with help, and then the stuff beyond that. Perkins talked about attitudinal factors – movers, tinkerers and stoppers. Stoppers stop and give up in the face of difficulty, tinkers fiddle until it works and movers actually make good progress and know what’s going on. The final aspect of methodology was inductive theory construction, while I’ll let you look up.

Think-aloud protocol requires the student to clearly vocalise what they were thinking about as they completed computation tasks on a computer, using retrospective interviews to address those points in the videos where silence, incomprehensibility or confused articulation made interpreting the result impossible. The scaffolding involve tutoring, task performance and follow-up. The programming tasks were in a virtual world-based pogromming environment to solve tasks of increasing difficulty.

How did they progress? Jacquie uses the term redirection to mean that the student has been directed to re-examine their work, but is not given any additional information. They’re just asked to reconsider what they’ve done. Some students may need a spur and then they’re fine. We saw some examples of students showing their different progression through the course.

Jacquie has added a new category, PLANNERS, which indicates that we can go beyond the Movers to explain the kind of behaviour we see in advanced students in the top quartile. Movers who stretch themselves can become planners if they can make it into the Zone of Proximal Development and, with assistance, develop their knowledge beyond what they’d be capable of by themselves. The More Competent Other plays a significant role in helping people to move up to the next level.

Full marks to Tony. Presenting someone else’s work is very challenging and you’d have to be a seasoned traveller to even reasonably consider it! (It was very nice to see the lead author recognising that in the final slide!)

 

ITiCSE 2014, Day 3, Session 6A, “Digital Fluency”, #ITiCSE2014 #ITiCSE

Posted: June 25, 2014 | Author: | Filed under: Education | Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , | Leave a comment
I'm at the Ångstrom Laboratory of Uppsala so this portrait hangs in the main hall. Hi, Anders!

I’m at the Ångstrom Laboratory of Uppsala so this portrait hangs in the main hall. Hi, Anders!

The first paper was “A Methodological Approach to Key Competences in Informatics”, presented by Christina Dörge. The motivation for this study is moving educational standards from input-oriented approaches to output-oriented approaches – how students will use what you teach them in later life. Key competencies are important but what are they? What are the definitions, terms and real meaning of the words “key competencies”? A certificate of a certain grade or qualification doesn’t actually reflect true competency is many regards. (Bologna focuses on competencies but what do really mean?) Competencies also vary across different disciplines as skills are used differently in different areas – can we develop a non-normative approach to this?

The author discussed Qualitative Content Analysis (QCA) to look at different educational methods in the German educational system: hardware-oriented approaches, algorithm-oriented, application-oriented, user-oriented, information-oriented and, finally, system-oriented. The paradigm of teaching has shifted a lot over time (including the idea-oriented approach which is subsumed in system-oriented approaches). Looking across the development of the paradigms and trying to work out which categories developed requires a coding system over a review of textbooks in the field. If new competencies were added, then they were included in the category system and the coding started again. The resulting material could be referred to as “Possible candidates of Competencies in Informatics”, but those that are found in all of the previous approaches should be included as Competencies in Informatics. What about the key ones? Which of these are found in every part of informatics: theoretical, technical, practical and applied (under the German partitioning)? A key competency should be fundamental and ubiquitous.

The most important key competencies, by ranking, was algorithmic thinking, followed by design thinking, then analytic thinking (must look up the subtle difference here). (The paper contains all of the details) How can we gain competencies, especially these key ones, outside of a normative model that we have to apply to all contexts? We would like to be able to build on competencies, regardless of entry point, but taking into account prior learning so that we can build to a professional end point, regardless of starting point. What do we want to teach in the universities and to what degree?

The author finished on this point and it’s a good question: if we view our progression in terms of competency then how we can use these as building blocks to higher-level competencies? THis will help us in designing pre-requsitites and entry and exit points for all of our educational design.

The next talk was “Weaving Computing into all Middle School Disciplines”, presented by Susan Rodger from Duke. There were a lot of co-authors who were undergraduates (always good to see). The motivation for this project was there are problems with CS in the K-12 grades. It’s not taught in many schools and definitely missing in many high schools – not all Unis teach CS (?!?). Students don’t actually know what it is (the classic CS identify problem). There are also under-represented groups (women and minorities). Why should we teach it? 21st century skills, rewordings and many useful skills – from NCWIT.org.

Schools are already content-heavy so how do we convince people to add new courses? We can’t really so how about trying to weave it in to the existing project framework. Instead of doing a poster or a PowerPoint  prevention, why not provide an animations that’s interactive in some way and  that will involve computing. One way to achieve this is to use Alice, creating interactive stories or games, learning programming and computation concepts in a drag-and-drop code approach. Why Alice? There are many other good tools (Greenfoot, Lego, Scratch, etc) – well, it’s drag-and-drop, story-based and works well for women. The introductory Alice course in 2005 started to attract more women and now the class is more than 50% women. However, many people couldn’t come in because they didn’t have the prerequisites so the initiative moved out to 4th-6th grade to develop these skills earlier. Alice Virtual Worlds excited kids about computing, even at the younger ages.

The course “Adventures in Alice Programming” is aimed at grades 5-12 as Outreach, without having to use computing teachers (which would be a major restriction). There are 2-week teacher workshops where, initially, the teachers are taught Alice for a week, then the following week they develop lesson plans. There’s a one-week follow-up workshop the following summer. This initiative is funded until Summer, 2015, and has been run since 2008. There are sites: Durham, Charleston and Southern California.  The teachers coming in are from a variety of disciplines.

How is this used on middle and high schools by teachers? Demonstrations, examples, interactive quizzes and make worlds for students to view. The students may be able to undertake projects, take and build quizzes, view and answer questions about a world, and the older the student, the more they can do.

Recruitment of teachers has been interesting. Starting from mailing lists and asking the teachers who come, the advertising has spread out across other conferences. It really helps to give them education credits and hours – but if we’re going to pay people to do this, how much do we need to pay? In the first workshop, paying $500 got a lot of teachers (some of whom were interested in Alice). The next workshop, they got gas money ($50/week) and this reduced the number down to the more interested teachers.

There are a lot of curriculum materials available for free (over 90 tutorials) with getting-started material as a one-hour tutorial showing basic set-up, placing objects, camera views and so on. There are also longer tutorials over several different stories. (Editor’s note: could we get away from the Princess/Dragon motif? The Princess says “Help!” and waits there to be rescued and then says “My Sweet Prince. I am saved.” Can we please arm the Princess or save the Knight?) There are also tutorial topics on inheritance, lists and parameter usage. The presenter demonstrated a lot of different things you can do with Alice, including book reports and tying Alice animations into the real world – such as boat trips which didn’t occur.

It was weird looking at the examples, and I’m not sure if it was just because of the gender of the authors, but the kitchen example in cooking with Spanish language instruction used female characters, the Princess/Dragon had a woman in a very passive role and the adventure game example had a male character standing in the boat. It was a small sample of the materials so I’m assuming that this was just a coincidence for the time being or it reflects the gender of the creator. Hmm. Another example and this time the Punnett Squares example has a grey-haired male scientist standing there. Oh dear.

Moving on, lots of helper objects are available for you to use if you’re a teacher to save on your development time which is really handy if you want to get things going quickly.

Finally, on discussing the impact, one 200 teachers have attend the workshops since 2008, who have then go on to teach 2900 students (over 2012-2013). From Google Analytics, over 20,000 users have accessed the materials. Also, a number of small outreach activities, Alice for an hour, have been run across a range of schools.

The final talk in this session was “Early validation of Computational Thinking Pattern Analysis”, presented by Hilarie Nickerson, from University of Colorado at Boulder. Computational thinking is important and, in the US, there have been both scope and pedagogy discussions, as well as instructional standards. We don’t have as much teacher education as we’d like. Assuming that we want the students to understand it, how can we help the teachers? Scalable Game Design integrates game and simulation design into public school curricula. The intention is to broaden participation for all kinds of schools as after-scjool classes had identified a lot of differences in the groups.

What’s the expectation of computational thinking? Administrators and industry want us to be able to take game knowledge and potentially use it for scientific simulation. A good game of a piece of ocean is also a predator-prey model, after all. Does it work? Well, it’s spread across a wide range of areas and communities, with more than 10,000 students (and a lot of different frogger games). Do they like it? There’s a perception that programming is cognitively hard and boring (on the congnitive/affective graph ranging from easy-hard/exciting-boring) We want it to be easy and exciting. We can make it easier with syntactic support and semantic support but making it exciting requires the students to feel ownership and to be able to express their creativity. And now they’re looking at the zone of proximal flow, which I’ve written about here. It’s good see this working in a project first, principles first model for these authors. (Here’s that picture again)

Figure from A. Repenning, "Programming Goes to School", CACM, 55, 5, May, 2012.

Figure from A. Repenning, “Programming Goes to School”, CACM, 55, 5, May, 2012.

The results? The study spanned 10,000 students, 45% girls and 55% boys (pretty good numbers!), 48% underrepresented, with some middle schools exposing 350 students per year. The motivation starts by making things achievable but challenging – starting from 2D basics and moving up to more sophisticated 3D games. For those who wish to continue: 74% boys, 64% girls and 69% of minority students want to continue. There are other aspects that can raise motivation.

What about the issue of Computing Computational Thinking? The authors have created a Computational Thinking Pattern Analysis (CTPA) instrument that can track student learning trajectories and outcomes. Guided discovery, as a pedagogy, is very effective in raising motivation for both genders, where direct instruction is far less effective for girls (and is also less effective for boys).

How do we validate this? There are several computational thinking patterns grouped using latent semantic analysis. One of the simpler patterns for a game is the pair generation and absorption where we add things to the game world (trucks in Frogger or fish in predator/prey) and then remove them (truck gets off the screen/fish gets eaten). We also need collision detection. Measuring skill development across these skills will allow you to measure it in comparison to the tutorial and to other students. What does CTPA actually measure? The presence of code patterns that corresponded to computational thinking constructs suggest student skill with computational thinking (but doesn’t prove it) and is different from measuring learning. The graphs produced from this can be represented as a single number, which is used for validation. (See paper for the calculation!)

This has been running for two years now, with 39 student grades for 136 games, with the two human graders shown to have good inter-rater consistency. Frogger was not very heavily correlated (Spearman rank) but Sokoban, Centipede and the Sims weren’t bad, and removing design aspects of rubrics may improve this.

Was their predictive validity in the project? Did the CTPA correlate with the skill score of the final game produced? Yes, it appears to be significant although this is early work. CTPA does appear to be cabal of measuring CT patterns in code that correlate with human skill development. Future work on this includes the refinement of CTPA by dealing with the issue of non-orthogonal constructs (collisions that include generative and absorptive aspects), using more information about the rules and examining alternative calculations. The group are also working not oils for teachers, including REACT (real-time visualisations for progress assessment) and recommend possible skill trajectories based on their skill progression.

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